Prior to the weaving loom and sewing machines, a factory might be able to make like 20 t-shirts a day with 50 workers. After mass production, factories generally employ the same amount of workers, but people aren't hand-sewing things. Instead roughly 50 people are producing thousands of tshirts a day leveraging giant machines.

Most of HN recognized the "We're firing people because AI makes people efficient" as one of the stupidest sales pitches ever and the CEOs that fell for it are just poorly ran companies that outed themselves.

AI is just another cycle in technology that is genuinely useful. The companies that are going to jump the gap are those that are hiring to use this new skill. If 10 workers pre-AI yields you 10x, and post AI yields you 100x, you don't cut down to 1 worker so you can keep delivering 10x. You invest, ruthlessly train, hire, and surge forward and leave your competition in the dust.

If there was 100x on the table for you, why weren't you already at 100x scale just with more headcount? That is the other side of this coin. Demand is a factor. Productivity goes up? Great, if there is demand to satiate that you can meet. I doubt that is the case otherwise you'd already have scaled to meet it if it were actually on the table for the taking if only you could output more volume.

The sewing machine analogy is a good one. The problem I'm seeing is leadership who sees the t-shirt company succeed with sewing machines, so goes out, buys 100 sewing machines, then puts them in the kitchen because they are a bakery and gets confused why the bread production isn't improving.

Because AI can do some things. Not everything. Applying it to the wrong problem reduces productivity.

  > If 10 workers pre-AI yields you 10x, and post AI yields you 100x, you don't cut down to 1 worker so you can keep delivering 10x.